Monitoring changes in linear models

By Lajos Horv'ath, Marie Husková, Piotr Kokoszka, Josef G. Steinebach. 2004

213 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8d9218e79cdfa522d7d3adf281b6dee2a58accfb

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In Control and Systems Engineering

In Statistics and Probability

Citations in the corpus

Change-Point Monitoring in Linear Models (2006, unknown): “1 of Horváth et al. (2004) and (10) yield that there are random variables k0 and m0 such that, for all k ≥ 1, ∣∣∣∣ m+k ∑ i=m+1 xi − kc1 ∣∣∣∣ ≤ k0(m1−κ + (m + k)1−κ ) if m ≥ m0, (28)”
DEPENDENT FUNCTIONAL LINEAR MODELS WITH APPLICATIONS TO MONITORING STRUCTURAL CHANGE (2014, unknown): “Examples of threshold functions can be found in Chu, Stinchcombe, and White (1996), Horváth et al. (2004) and Aue, Horváth, and Reimherr (2009b), among others.”
Structural breaks in time series (2013, methodology): “…the null), that is, sn ¼ inffk 1 : jCnðkÞj gnðkÞg: Sequential tests based on CUSUM-based detector functions were considered in Aue et al. (2006, 2009) and Horváth et al. (2004) for linear and time series regressions, in Gombay and Serban (2009), Hušková et al. (2007) for AR processes, and in…”
Bootstrapping sequential change-point tests for linear regression (2012, background): “[10] on the behavior of the test statistics related to the above introduced test procedure.”
A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals (2005, background): “…the power (or size) of the procedure rather evenly (if no further knowledge about the location of potential shifts is available) or directs it at the (potential) timing of the shift (see Horváth et al., 2004; Zeileis et al., 2005, for a more detailed discussion of boundaries for monitoring).”
Delay times of sequential procedures for multiple time series regression models (2009, methodology): “Simulations in Horváth et al. (2004) have, however, indicated that the test procedures perform rather conservative for sizes of the training period less than or equal to 100 and suggested that one trims the asymptotic critical values by 10% in an effort to improve the finite sample behavior.”
Bootstrapping Sequential Change-Point Tests (2008, methodology): “In the next section we give the asymptotics based on which the critical value has been chosen by Horváth et al. (2004) and propose some alternative methods based on bootstrapping.”